Media, Messages & Mobility

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Anthropologist Michael Wesch, noted for his studies of YouTube and video sharing states, “when media change, then human relationships change”.

Today, at the DevLearn2010 social media camp, I will be conducting a discussion with my Internet Time Alliance colleagues on mobile learning, but I would like to focus on how the mobile medium changes our relationships with sharing knowledge, connecting with others and getting things done.

For example, what does mobile technology do to how we seek knowledge, make sense of it and share with others?

Video [created and shared via mobile devices] is becoming an important medium of personal communication, evidenced by John Seely Brown’s example of a surfing community of practice as well as Chris Anderson’s examination of how web video powers innovation.

The big question is NOT how to blend mobile learning into our suite of existing tools, but rather what effect does this significant shift in the power of knowledge creation and sharing have on our understanding of workplace learning?

Collaboration is work

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As I get together with my Internet Time Alliance colleagues here in California, I really appreciate all of the connecting and conversing we’ve done over the past two years, as our shared experiences ease the path to further collaboration. Working collaboratively and effectively is a challenge for all organizations and must be continuously renegotiated as conditions change. Collaboration is not the same as cooperation. Collaboration is working together and achieving a shared objective. Collaboration puts cooperation to the test, with outcomes, objectives and responsibilities; constrained by time, resources and priorities.

Here are some collected thoughts on collaboration from others:

100 Web Tools to Enhance Collaboration (Part 3) | Ozge Karaoglu’s Blog

“If you have an apple and I have an apple and we exchange these apples then you and I will still each have one apple. But if you have an idea and I have an idea and we exchange these ideas, then each of us will have two ideas.” George Bernard Shaw

Network Weaving: The 4 Laws of Networks

The pragmatic reality is that innovation happens at the intersection of learning and cultivating diverse connections. When you have diverse connections in a network, learning almost cannot not happen. Networks literally become learning disabled if the connections become too homophilous and without learning, no innovation is possible.

ME2: Horizontal Collaboration « TheBrycesWrite

It is also important to point out that advocating Enterprise 2.0 / social collaboration isn’t necessarily the equivalent to denouncing all forms of Vertical Collaboration. Each have their value and their place for particular types of work. Advocating Enterprise 2.0 / social collaboration is the recognition that we’ve found something effective at filling in the knowledge gaps left by traditional Vertical Collaboration methods that prevent organizations from maximizing the capacity of their people. Thus, encouraging the use of capabilities and behaviors that fill those gaps – Web 2.0 / social media inspired methods proving to be effective for Horizontal Community Collaboration – will complement your traditional collaboration methods well.

At the Corner of Assertiveness & Cooperation: Collaboration > Trust Matters

Collaboration gets its power because it uses the energy of Assertiveness–ideas and real points of view, championed by people who care–and the energy of Cooperation–a willingness to make things work for all involved. From collaboration comes the best result, the idea or solution which is fashioned from everyone’s input and is better than what any one person could have come up with on her or his own.

Esko Kilpi Oy / www.kilpi.fi

Connections are not enough. Third threshold is true conversation. For connected thinking to occur, for both sides to find meaning in the interaction, participants must create a common context: What is it we are here to do? This takes time. Conversations cannot be hurried. Conversations cannot be tightly scripted and agenda based meetings separated from the practice of work. Knowledge work is talking and listening! The real challenge today is slowing down our thinking processes and increasing awareness of the thinking behind our actions and the assumptions behind our thinking.

Collaboration – If it Were That Easy We Would all Do It – Well

Will we ever learn? We place new labels on the issue (it’s not KM anymore, now its collaboration); new products emerge (SharePoint: “it does everything”), and all too often forget the lessons of the past. We believe that the “new focus” and/or the new technology will deliver on the promise without requiring any strategy.

Wise and interesting words

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Here are some of the things I learned via Twitter this past week.

So the writer who breeds more words than he needs, is making a chore for the reader who reads. Dr. Seuss; via @nancyrubin

@GregoryLent : “We are shipping factories, jobs and wealth overseas so rapidly that it is hard to even comprehend what is going on.”

@Complexified : “Complexity demands new levels of relationship building skills. How we work together shares wisdom deeper than any one of us.” via @betseymerkel

“You can’t teach critical thinking without critical situations.” via @ethanbodnar

Higher education: “the mass production of people literally unfit for anything except to take part in an elaborate charade.” via @anya1anya

“Since the way we run universities now is such a train wreck, what’s a better way?” by @danpontefract

I believe the education teaching process at high school and higher education levels need to radically shift. In both environments, I recommend teaching the theory of various subjects for half the day, and the other half is spent working on the amalgamation of subject-matter through application. That’s right – half the time in theory and half the time applying said theory in real world, critical thinking, cross-collaborative, multi-discipline ways that allow the student to actually practice ‘learning by doing’ concepts whilst learning the theory.

“If nothing else, I hope my book gets rid of learning styles” – Ruth Clark about her book Evidence-Based Training Methods; via @hjames

Thanks to a growing body of research evidence, we’ve learned a great deal in the last 20 years about which methods really work when training people. Yet many trainers are still using time-honored methods and assuming that they work — despite recent evidence to the contrary.

Interesting mind map on how decisions are made. by @jackvinson

I was Wrong.  by @timkastelle

In other words, to be innovative, we have to be wrong a lot. Being wrong is the first step towards being right.

Don’t hide your mistakes, learn from them. If every idea that you try works, it’s a sure sign that you’re not trying enough ideas.

What’s the relationship between R&D spending and Innovation? by @MartijnLinssen – Return on R&D

We can only simply notice that Apple is a very innovative company, for example. SAP spending 4 or 5 times as much on R&D doesn’t make them 4-5 times as innovative (I’m fairly sure even that no one could handle a company being 5 times as innovative as Apple).
Most R&D is window dressing and aimed to please the shareholder – not the stakeholder, that much Larry Ellison did prove in his speech at Oracle Open World.

A curved path to social learning

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When I was introduced to Charles Jennings’ C-Curve for learning & development (L&D) I wrote about it in the transition to networked accountability.

Charles’ C-Curve is a model in practice, based on his experience as CLO of Reuters. I see a parallel between this migration of the L&D department and the social order necessary to do certain types of group work [Refs: Cynefin – TIMN]

  1. L&D Autonomous = taking action as a Tribe of its own
  2. L&D Aligned with organization = coordinated with the Institution
  3. L&D with governance & guidelines = able to work in a collaborative Market
  4. L&D strategically aligned = a co-operative member of (a) Network(s)

I wondered if tribal organizations may be able to thrive in networks because they are already used to more freedom. I have noticed that it is difficult to convince organizations steeped in the institutional models that the networked model may be better to deal with growing complexity. Also, those who already have to respond to markets may understand the value of networks much better than institutions. Hence the advantage of the private sector in adapting new work models before the public sector.

In organizations and complexity, I discussed three archetypal organizational models and some of their defining characteristics.

Simplicity Complication Complexity
Organizational Theory Knowledge-Based View Learning Organization Value Networks
Attractors Stakeholders (vision) Shareholders (wealth) Clients (service)
Growth Model Internal Mergers & Acquisitions Ecosystem
Knowledge Acquisition Formal Training Performance Support Social
Knowledge Capitalization Best Practices Good Practices Emergent Practices

I’ve combined the C-Curve [X=Autonomy, Y= Strategic Alignment] with the knowledge acquisition models from these three organizational types in the figure below. The question that I ask here is whether it is necessary to follow the curve or if one can leap from Stage 1 to 4.  If not, that means that organizations need to understand and implement something like a human performance technology model for L&D before they can move on to social learning. Perhaps this is why social learning is being resisted or put into a formal training box in many organizations. They have not made the move to Stage 3 (Performance Support) yet. It’s too much of a leap for organizations in Stage 2. On the other hand, social learning is only a short leap for more tribal start-ups that have not developed any structure at all for L&D as they are quite comfortable with autonomy and messy networks. Stage 2 seems like the worst place to be.

Spiky Networks

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Richard Florida’s Creative Class blog reports that certain areas of the USA have a much higher use of social media than others. There are significant differences between California and Oklahoma, for example. Check out the map of the American Spiky Social Network.

The level of geographic concentration is pronounced, though the leading social media metros are not surprising. San Francisco and San Jose, Silicon Valley, top the list, with New York City, Austin, Boston, Seattle, Denver, Salt Lake City, L.A., and Atlanta rounding out the top 10.

I did a quick check of visitors to this blog over the past few months and it almost mirrors these results, with California, New York & Texas leading. This may be due to population but I find it a rather interesting coincidence.

Patterns emerge over time

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Andrew Cerniglia has an excellent article that weaves complexity, cynefin and the classroom together. It is worth the read for anyone in the teaching profession. I became interested in complexity as I moved outside the institutional/corporate walls and was able to reflect more on how our systems work. The observation that simple work is being automated and complicated work is being outsourced seems rather obvious to me now. Complex work has increasing market value in developed countries and that is where the future lies. However, our schooling, training and job structures do not support this.

Cerniglia explains how complex the classroom can be, when we factor in the outside that touches each student daily:

But there is another, most important factor, life outside of the classroom. What happens beyond the classroom walls, in other classes, and more significantly outside of school, affects each learner. The combination of these variables supports the idea that classrooms should be classified as “complex” with the Cynefin Framework. If we review the traits of “Complex” systems, it is clear that often times there is “no right answer” in terms of instructional choices, that classrooms are “systems in constant flux”, and that the “ability to understand” (from the teacher’s perspective) comes after class has been dismissed.

This is the situation for many people outside the classroom, whether at work or in general life: there is no right answer. Cerniglia has created an excellent concept map that summarizes the cynefin framework and is worth exploring.
Here is a detail from the map:

The patience to watch patterns emerge over time is almost non-existent, though it’s what I’ve been able to do as a freelancer, and perhaps less engagement on a job site is part of the future of work. Furthermore, there are organizations that send tacit and explicit signals which could  result in these dangers:

  • The desire to revert to simple strategies, like simple PowerPoint presentations, executive summaries and three-phased operations.
  • Impatience with results that take more than one fiscal quarter to materialize.
  • Over-control of staff and resources, negating workers’ innate need for autonomy, mastery and purpose.

A strategy of probe-sense-respond (P-S-R) means testing things out and taking action before all the data are available or fully analyzed. So far, one of the few places I’ve noticed a P-S-R approach is in web development, especially with software as a service, like Google, where not-fully-baked applications get released and are then relentlessly analyzed in action. P-S-R is the mindset for life in perpetual Beta.

Is research racing to the middle?

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From the annual report of the New Brunswick Innovation Foundation [my emphasis]:

Large amounts of public funding are available for researchers to get started. Large amounts of capital are also available for companies when they reach their growth stage, after they have taken flight. Banks make loans and, and stock markets offer IPO’s.

What about that fledgling point in between? Very little.

This graphic shows there is much more available funding for Fundamental Research (left) then (left to right) Applied Research; Proof of Concept; Seed Capital & Early Stage Venture Capital; hence NBIF’s focus on these. Venture Capital & Growth Capital are represented as much larger as well.

My own observations are showing this may not be the case, but I haven’t done extensive research. However, one of the primary funding agencies for fundamental research (e.g. discovery grants) is NSERC, which is definitely moving toward applied research, as reported by CBC:

Funding involving industry now represents about one third of NSERC’s budget, and is expected to grow. The agency wants to double both the number of academic-industry partnerships and industry participation rates in NSERC programs by 2014-15, Walden said.

‘These sponsors aren’t paying for the research out of philanthropy. They want results.’— Janet Walden, NSERC

She presented the figures as part of a panel titled “Universities as economic powerhouses: industry-academic collaborations” at the Canadian Science Policy Conference in Montreal.

Other agencies, such as Canada’s NRC and ACOA’s Atlantic Innovation Fund also fund applied research

The purpose of the Atlantic Innovation Fund is to:

  • increase research and development (R&D) being carried out in Atlantic Canada research facilities leading to the launch of new products, processes and services;
  • improve the region’s capacity to commercialize R&D;
  • strengthen the region’s innovation system by supporting R&D and commercialization partnerships and alliances among private sector enterprises, universities, research institutions and other organizations in Atlantic Canada; and
  • enhance the region’s ability to access national R&D programs.

Perhaps the NBIF graphic no longer portrays the situation in Canada. If significantly less money goes toward fundamental research, what will happen to the innovation continuum? I wonder if we are racing to the middle and in our quest to be “innovative” we are forgetting the basic research that fuels all innovation. One example is that for the widely-used Global Positioning System (GPS) to work you need to employ both theories of relativity. Now who would have thought of that application when those theories were first put forth?

Network Learning: Working Smarter with PKM

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“In the period ahead of us, more important than advances in computer design will be the advances we can make in our understanding of human information processing – of thinking, problem solving, and decision making …” – Herbert Simon, Economics Nobel-prize winner (1968)

The World Wide Web is changing how many of us do our work as we become more connected to information and each other. In California, Ray Prock, Jr. (2010) uses a Web-based note system to store messages, manage his financial risk and stay on top of the multiple factors necessary to run a successful dairy farm. He is constantly learning as he works and has found a method to keep up, thanks to the Internet.

For many, however, keeping up isn’t easy. The amount of information flowing through the Internet today is measured in exabytes, or billions of gigabytes. We now create as much data in days as it took us centuries to create in the past.

This information overload has a direct impact on workplace learning. Workers have access to more information than ever before, but often don’t know if it’s the right information or if it’s current. In the industrial workplace, our training programs could prepare us for years of work, but much of what we learn today will be outdated in months or even weeks.

We need to re-think workplace learning for a networked society. Our organizational structures are becoming more decentralized, with individual access to almost unlimited information, distributed work teams, and digital media that can be copied and manipulated infinitely. In the interconnected workplace, who we know and how we find information are becoming more important than what we know.

As the Internet Time Alliance’s Jay Cross says, formal learning can be somewhat effective when things don’t change much and are predictable, but today’s world is the opposite in every way imaginable. Things are changing amazingly fast, and there’s so much to learn. Today’s work is all about dealing with novel situations (Cross 2010a).

Jane Hart, another colleague at the Internet Time Alliance, has examined social media and learning in the context of the workplace and has noted that much of it is informal (Hart 2010). Formal, structured learning plays only a small role in getting things done in the networked workplace. Research shows that about 80 percent of workplace learning is informal (Cross 2010b) and that less than 10 percent of what knowledge workers need to know for their jobs is in their heads (Kelley 1999).

Informal learning is nothing new, but it is of growing importance in the modern, digitally connected workplace. Making sense of information, both personally and in networks, is becoming a key part of work. Teams and organizations that can share information faster and make better sense of it are more productive. Social learning is about getting things done in networks. More attention must be paid to how we can support and encourage informal learning in the workplace. A “workscape” focus is  broader than the traditional training and development approach.

Personal Knowledge Mastery

Personal knowledge mastery (PKM) is an individual, disciplined process by which we make sense of information, observations and ideas. In the past, self-directed learning may have involved keeping a journal, writing letters or having conversations. These are still valid, but with digital media we can add context by categorizing, commenting on, or even remixing information. We can also store information for easy retrieval as we need it.

PKM, at the individual level, includes:

Personal directed learning – how individuals can use social media for their own (self-directed) personal or professional learning; and

Accidental and serendipitous learning – how individuals, by using social media, can learn without consciously realizing it (e.g., incidental or random learning).

At its core, PKM is a way to deal with an ever-increasing amount of digital information. It requires an open attitude toward learning and finding new things. Each worker needs to develop individualized processes of filing, classifying and annotating information for later retrieval.

Standard document management methods have been shown to fail over the years, as most workers do not personally adopt them. Developing good network learning skills, on the other hand, can aid in observing, thinking and using information and knowledge. Learning in networks also prepares the mind to be open to new ideas and can result in “enhanced serendipity.” As Louis Pasteur said, chance favors the prepared mind.

One way to look at network learning is as a continuous process of seeking, sensing and sharing.

Seeking is finding things out and keeping up to date. Building a network of colleagues is helpful in this regard—it not only allows us to “pull” information, but also have it “pushed” to us by trusted sources.

Sensing is how we personalize information and use it. Sensing includes reflection and putting into practice what we have learned. Often it requires experimentation, as we learn best by doing.

Sharing includes exchanging resources, ideas and experiences with our networks and collaborating with our colleagues.

Seeking: Using Filters

In seeking, we need to develop effective filters so we are not overwhelmed by too much information. A high signal-to-noise ratio is desirable.

We can use human filters, such as asking a close colleague for a good source of information on a subject. This often happens in open work environments, where someone asks the group, “Hey, does anybody know how to … ?” This is a naïve filter, in that the recommendations provided are not necessarily reliable. The closest people are not always the best sources of knowledge.

Another option is to find a known expert in a field and ask him or her for advice. It’s a better approach, but dependent on the expert.

The best option is to connect with a network of expertise and corroborate advice from a variety of experts. Twitter is an example of a platform that enables this. We can follow many people in a discipline and fine-tune the network by adding or subtracting from it until we have an optimal signal-to-noise ratio.

There are also tools that use mechanical filters, such as search engines or analytical engines that show trending topics. Using both human and mechanical filters can ensure a good flow of information without being overwhelmed. Keyword alerts can be set up with a variety of online systems, or regular searches can be conducted on social media platforms. With practice, we can find what we need when we need it (and sometimes before we need it).

Sensing: Validating, Synthesizing, Presenting, and Customizing

We make sense of data by using our existing knowledge to create more information. This is what writers do—they take various data and write a coherent narrative that becomes information for someone else. While this is an efficient way of transmitting information from one to many, it does not transfer knowledge, as a recipe book does not a chef make. Each person makes sense and builds expertise on his or her own terms.

As mentioned, filtering information is an easy way to start to make sense of digital information flows. Social bookmarking services, such as Delicious, enable us to categorize and annotate Web pages. Social bookmarks are searchable and can be shared within a group or made public. They are a good initial step toward moving information to the cloud. Making information public helps to validate it, as we can check references, analyze logic and compare sources.

Another level of value can be added by synthesizing information. This synthesized information can then be presented in various digital formats to facilitate understanding. For example, a good graphic may make more sense than several pages of text. A slide show with voice-over can help convey complex ideas. Information presentations can be further customized for specific contexts, such as an analysis of global trends and how they may affect a specific business.

These are examples of taking information and adding value to it for the individual, the group, the organization and the network. By treating information as grist for our cognitive mills, we can build knowledge bases that will help us get work done. Thus, a blog can become a place for small, coherent thoughts that, when aggregated, become a discussion document or a policy paper.

Without the ongoing process of sense making, we can fall into the trap of grabbing the easiest information that is available at the time.

Some Web tools for sense making include:

Note taking (e.g., EverNote)
Social bookmarks (e.g., Delicious)
Micro-sharing (e.g., Twitter)
Blogs (e.g., WordPress)
Presentations (e.g., Slideshare)
Videos (e.g., Vimeo)

Not everyone will use all of these tools, and there are many others, but it is important to develop methods of sense making that work on a day-to-day basis.

Sharing: Joining a Community

PKM practices are part of a social learning contract for better organizational learning. Sharing is an essential part of network learning. Without it, we become islands of knowledge that cannot take collective action.

The use of online media enables sharing and can result in exponential network effects. Because knowledge has no known limits, the potential return on investment in knowledge co-creation can be many orders of magnitude greater than traditional process improvement methods.

The most wonderful aspect of Web-based social media is that they are designed for sharing. We can start our sense-making journey in a completely selfish way, but by using Web tools we can easily share whenever we wish. This is network learning. For example, blogs can start as private journals, but after a while we may want to share our posts. As the blog is already online, it can be made public, and all of the information it contains is available for distribution. No extra programming is necessary.

By sharing information and engaging in online conversations, we become part of a community. We will discover that we are truly in a community of practice when it changes our practice.

By seeking, sensing and sharing on an individual basis, we create the building blocks for a dynamic community of knowledge workers, continuously pushing at the edges of our disciplines. Network learning lays the foundation for the ongoing process of idea management, a necessity in complex work environments that require continuous adaptation. This sharing and using of ideas is at the core of business innovation.

REFERENCES

Cross, Jay. 2010a. How to Support Informal Learning Informal Learning Blog.

Cross, Jay. 2010b. Where Did the 80% Come From? Informal Learning Blog

Hart, Jane. 2010. The State of Learning in the Workplace Today. Centre for Learning & Performance Technologies.

Kelley, Robert E. 1999. How to be a Star at Work. New York: Crown Publishing Group.

Prock, Ray, Jr. 2010. Ray-Lin Dairy: A Progressive California Dairy Farm Blog.

Note:

This article was published, with minor changes, as PKM: Working and Learning Smarter, in Information Outlook, The Magazine of the Special Libraries Association, Sept 2010.

"The Internet is a serendipity creation machine"

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Here are some of the things I learned via Twitter this past week:

Benoit Mandelbrot died this week:

Why Mandelbrot matters “the market is not rational at all”:

“A few fund managers have experimented with these concepts [of price dependence, whatever that is, and volatility]. They often call it chaos theory – though strictly speaking that is marketing language riding on the coat-tails of a popular scientific trend. In reality, the mathematics is still young, the research barely begun, and reliable applications still distant.”

“Fractal joke! RT @Ihnatko: RIP Benoit Mandelbrot. Thank God he wasn’t murdered. It would’ve taken the cops forever to draw the chalk outline” via @stevenbjohnson

—

“The Internet is a serendipity creation machine.” @johnrobb

“Air sandwich = empty space between top of organization and the doers at the bottom.” @jaycross

“Old paradigm: analysis, strategy only. New: those PLUS storytellng, improvisation, movement/embodiment & visual thinking.” @CreatvEmergence

“I’ve had 7 managers in 5 years. None of them know what I do. The only thing they’ve ever done is try to get me to train someone else.” @NatashaChart

@hrheingold: “Great slideshow by @corinnew on building a personal learning network”

PLN’s are deliberately formed networks of people and resources capable of guiding our independent learning goals and professional development needs.

Bilingualism Good for the Brain : Discovery News via @jalam1001

Bialystock has shown that bilinguals do better at tests that require multitasking, including ones that simulated driving and talking on a phone.

“Make no mistake: Everybody is worse,” Bialystock said, “but the bilinguals were less worse.”

“My rant on the futility of Q and A, with a nod to @hjarche” by @johnniemoore

Here’s my beef. The presentation itself sets up a status game in which the speaker and chairperson start and usually stay high and the audience is low. Here are the various ways this gets manifested. For starters, the speakers are usually at the front of the room and often on a raised platform. Before a word is said, they’re already in high status. Then the chairperson offers a flattering introduction; if we’re lucky they merely flatter the speaker but a lot of them have found ways to flatter themselves by implication. The speaker gets a microphone and the licence to talk pretty much unconstrained. If there’s a time limit, it’s rarely enforced …

Latest Learnlet: Serendipitous revisiting by @Quinnovator

So the point is that you have to keep putting ideas out there, again and again, to find the right time for them to take hold.  Not like advertising, but like offerings.  It’s not planned, it’s just at the idea strikes, but I reckon that’s a better heuristic than a more calculated algorithm. At least, if you are trying to inspire positive change, and I confess that I am.

New Era of Workplace Learning – “social learning is something you do” by @C4LPT

The term “social learning” therefore has a much wider meaning than simply “social training” – where the focus is on the creation, delivery and management of formal learning. “Social workflow learning” (as we might call it) is about workers sharing information and knowledge with others in networks and communities as well as adopting a new collaborative approach to working – in order to DO their jobs effectively.

Organizations and Complexity

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I’ve discussed this table before, but I’d like to put all the links together to highlight what we need to do with our organizations and structures to deal with complexity.

From the evolving social organization we developed this table to show the differences between three archetypal organizations.

Simplicity Complication Complexity
Organizational Theory Knowledge-Based View Learning Organization Value Networks
Attractors Stakeholders (vision) Shareholders (wealth) Clients (service)
Growth Model Internal Mergers & Acquisitions Ecosystem
Knowledge Acquisition Formal Training Performance Support Social
Knowledge Capitalization Best Practices Good Practices Emergent Practices

How we can support emergent practices in the increasingly complex enterprise:

COMPLEXITY

Patti Anklam, in discussing value networks and complexity  states:

Understanding of complexity provides a practical guide to managing context.

You can’t manage a network, you can only manage its context.

Slight alterations in the structure can create significant change over time;

But you must first look to understand the context

VALUE NETWORKS

Value network analysis is a process which is more art than science. Humans work in complex environments and we are by our very nature unpredictable. The result of a VNA allows you to ask better questions but it doesn’t give specific answers (it’s not a tool for bean counters). I think that VNA is an excellent change management tool. I can see the use of VNA and the resulting concept maps enabling better communication within organizations, with clients, with funders and throughout communities

CLIENTS (SERVICE)

I have met new friends, business partners and clients with social media, and like the authors of Trust Agents, I would say that a “no sales” approach works best in the long run. The chapter called the Human Artist covers online etiquette in detail and should be read by any self-described social media guru. Also, three of the book’s chapters reflect The Law of the Few – how small groups of people enable social change or the transmission of new ideas.

Connectors: They talk about the idea of being Agent Zero, or the person who connects groups where no previous connection exists.

Mavens: They also discuss creating value, or doing things that people need, one small bit at a time. In Make Your Own Game, the premise is to find a niche and become an expert in it.

Salespeople: In Build an Army, the authors show the promise and pitfalls of crowd-sourcing and social networks for business.

ECOSYSTEM

Most intelligent people know that there is no such thing as a job for life. Corporations have shown that loyalty to the enterprise does not work both ways. Organizations should look at how they can structure to take advantage of these workplace changes. The first part is to stop thinking like a hierarchy, with titles and reporting relationships, and start framing the enterprise in terms of networks. Mapping value networks is a start, as is talking about social networks and supporting them through the use of social media. If you look at work differently and talk about it differently, then new conversations and attitudes will result.

Here are some ideas, for starters:

Abolish the organization chart and replace it with a network diagram.

Move away from counting hours, to a results oriented work environment

Encourage outside work that doesn’t directly interfere with paid work, as it will strengthen the network

Provide options for workers to come and go and give them ways to stay connected when they’re not employed. Build an ecosystem or join one (e.g. an open source community).

SOCIAL

In a framework for the social enterprise we noted how knowledge workers get things done by conversing with peers, customers and partners, as they solve the problems of the day. Learning from these social interactions is a key to business innovation. To participate in their markets, organizations, customers and suppliers need to understand each other and this too, is social. Social learning is how knowledge is created, internalized and shared. It is how knowledge work gets done.

EMERGENT PRACTICES

The cynefin model shows that emergent practices are needed in order to manage in complex environments and novel practices are necessary for chaotic ones. Most of what we consider standard work today is being outsourced and automated. We are facing more complexity and chaos in our work because of our interconnectedness.

Many of the problems we face today are COMPLEX, and methods to solve simple and complicated problems will not work with complex ones. One of the ways we addressed simple & complicated problems was through training. Training works well when you have clear and measurable objectives. However, there are no clear objectives with complex problems. Learning as we probe the problem, we gain insight and our practices are emergent (emerging from our interaction with the changing environment and the problem). Training looks backwards, at what worked in the past (good & best practices), and creates a controlled environment to develop knowledge and skills.

To deal with increasing complexity, organizations need to support emergent work practices, in addition to their training efforts. They must support collaboration, communication, synthesis, pattern recognition and creative tension, all within a trusting environment in order to be effective.